Spreading Code Estimation Method for DS Signal Based on mldc and Bit-by-Bit Decision

Abstract

The present invention discloses a direct spread signal spreading code estimation method based on MLDC and bit-by-bit judgment, which solves the problem in the prior art that calculation complexity and estimation performance under the condition of low signal-to-noise ratio cannot be considered, and its realization includes: The mathematical model of the direct spread signal is established, and the inner product sum function constructed based on MLDC is used to make a bit-by-bit decision on the randomly generated sequence to be decided, and then the bit-by-bit decision is repeated to obtain the final spreading code estimation sequence. In the present invention, the inner product sum function directly characterizes the likelihood degree of the sequence to be judged and the spread spectrum code, and the bit-by-bit judgment method divides the sequence to be judged into two parts, the front and the rear, to judge respectively, and splicing to obtain the estimate of the spread spectrum code. The invention completes the estimation of the spread spectrum code of the direct spread signal in the non-cooperative spread spectrum communication, has good estimation performance under the condition of low signal-to-noise ratio, and has relatively low computational complexity. The present invention can be directly applied to non-cooperative spread spectrum communication systems, and can also be used in corresponding software radio and other systems.

Description

technical field [0001] The invention belongs to the technical field of signal processing, mainly relates to non-cooperative communication signal processing technology, specifically a method for estimating spreading codes of direct spread signals based on maximum likelihood decoding criterion (MLDC) and bit-by-bit judgment, mainly used for direct spread Extraction estimation of signal spreading code. Background technique [0002] Direct Sequence Spread Spectrum (DSSS) signals have low transmit power spectral density, strong anti-intercept and strong anti-interference characteristics, and can suppress multipath effects, so they are widely used in contemporary civil communications, military countermeasures, detection and navigation, GPS positioning, etc. in a field. The reconnaissance and deciphering of direct spread signals is one of the hotspots and difficulties in the field of communication countermeasures, especially in non-cooperative communications, if the correct spread...

AI Technical Summary

Problems solved by technology

[0006] (1) Establish the mathematical model of the baseband direct spread signal in segmented form: for the short code direct spread signal intercepted in the non-cooperative spread spectrum communication, in the chip width T c , information code cycle T d , spreading code length L, spreading period T s and asynchronous time τ parameter information have been determined, and the noise interference is equivalent to additive white Gaussian noise, the DS signal is calculated according to 1 / T c The frequency is sampled to obtain a discrete form of baseband synchronous short code direct spread signal In the formula, n represents the nth symbol of the baseband synchronous short code direct spread signal in discrete form, A represents the signal amplitude, d represents an independent and equal probability bipolar information code, k represents the kth information symbol, and N represents the information The number of symbols, c represents the spreading code, v represents the additive Gaussian white noise, and r(n) is segmented according to the window length of the spreading code length, and there are N segmented windows to obtain the segmented baseband Direct spread signal r=[r (1) ,r (2) ,...,r (N) ], set up the mathematical model of the baseband direct spread signal in segmented form;

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